System and method of stream processing workflow composition using automatic planning

ABSTRACT

An automatic planning system is provided for stream processing workflow composition. End users provide requests to the automatic planning system. The requests are goal-based problems to be solved by the automatic planning system, which then generates plan graphs to form stream processing applications. A scheduler deploys and schedules the stream processing applications for execution within an operating environment. The operating environment then returns the results to the end users.

This invention was made with Government support under Contract No. TIAH98230-04-3-0001 awarded by U.S. Department of Defense. The Governmenthas certain rights to this invention.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to stream processing and, inparticular, to workflow composition. Still more particularly, thepresent invention provides a method, apparatus, and program product forstream processing workflow composition using automatic planning.

2. Description of the Related Art

Stream processing computing applications are applications in which thedata coming into the system in the form of information flow, satisfyingsome restriction on the data. Note that volume of data being processedmay be too large to be stored and, therefore, the information flow mustbe processed on the fly. Examples of stream processing computingapplications include video processing, audio processing, streamingdatabases, and sensor networks.

Component-based Software Systems (CBSE) are concerned with thedevelopment of software intensive systems from reusable parts(components), the development of reusable parts, and system maintenanceand improvement by means of component replacement and customization, aswell as development a framework for component composition. Compositionmay be done statically or dynamically. This disclosure is concerned withdynamic component composition.

We are concerned with specific component based systems, in particularstream processing component based systems. All the composition detailsand information about how to glue together system from the components,and how to configure components, are stored in the workflow. Workflowcan provide in addition some extra information.

This approach enables increased code reuse, simplified development, andhigh flexibility of the system. Components may be interconnected inmultiple configurations, achieving highly complex functionality viacomposition of simpler black-box operations. Such architectures arebeing currently developed in many application areas, in particular,stream processing applications.

In the component based stream processing architectures, the streamprocessing applications are composed of several processing units orcomponents. The processing units can receive information streams on oneor more input ports and produce one or more output streams, which aresent out via output ports. The output streams are a result of processingthe information arriving via the input streams, by filtering,annotating, or otherwise analyzing and transforming the information.Once an output stream is created, any number of other components canread data from it. All processing units together compose a workflow. Astream processing application reads and analyzes primal streams cominginto the system and produces a number of output streams that carry theresults of the analysis.

Composing stream processing workflows is a labor-intensive task, whichrequires that the person building the workflow have an extensiveknowledge of component functionality and compatibility. In many cases,this makes it necessary for end-users of stream processing applicationsto contact application developers each time a new output informationstream is requested and, as a result, a new workflow is needed. Thisprocess is costly, error-prone, and time-consuming. Also, changes toother elements of the stream processing system may require changes tothe workflow. For example, processing units or primal streams may becomeunavailable, users may place certain restrictions on the output, orchanges may be made to the components themselves.

In large practical stream processing systems, both changes in the datacoming into the system and changes in the system configuration caninvalidate deployed and running stream processing applications. Withtime, these applications can start to produce output that no longersatisfies the user's requirements or they can be relying on primalstreams that have become inactive or some additional system changes likeadding new hardware or new components/processing units. In manysituations, users' requirements can be better satisfied if an existingworkflow is updated with newly available primal streams orcomponents/processing units. Therefore, when changes such as thosedescribed above occur, the workflow must be reconfigured quickly, beforeany potentially valuable streaming data is lost. Such timelyreconfiguration is extremely difficult to achieve if the workflowcomposition requires human involvement.

SUMMARY OF THE INVENTION

The present invention recognizes the disadvantages of the prior art and,in one illustrative embodiment, provides a method, in a streamprocessing system, for composing stream processing workflows usingautomatic planning. The stream processing system receives one or moreprimal streams and executes stream processing applications in a streamprocessing operating environment. The method comprises receiving arequest for stream processing, translating the request for streamprocessing into a formal expression of the request in a descriptionlanguage, and generating a workflow based on the formal expression ofthe request and a domain definition in the description language. Thedomain definition describes the stream processing operating environment.The workflow comprises nodes corresponding to stream processingapplication components with possible parameters values set and linkscorresponding to streams.

In another illustrative embodiment, the method further comprisesadapting the workflow into a stream processing application that isexecutable in the stream processing operating environment. In yetanother embodiment, the method further comprises deploying the streamprocessing application to the stream processing operating environment.

In one exemplary embodiment, the method further comprises storing thedomain definition in a planning cache.

In yet another illustrative embodiment, the method further comprisesreceiving a change notification that indicates one or more changes tothe domain definition and adjusting the workflow based on the one ormore changes to the domain definition to form an adjusted workflow. Inone exemplary embodiment, the method further comprises adapting theadjusted workflow into an adjusted stream processing application that isexecutable in the operating environment. In another exemplaryembodiment, the method further comprises deploying the adjusted streamprocessing application to the operating environment. In yet anotherexemplary embodiment, the method further comprises determining a newdomain definition in response to the change notification and storing thenew domain definition in the planning cache.

In another illustrative embodiment, a stream processing system composesstream processing workflows using automatic planning. The streamprocessing system receives one or more primal streams and executesstream processing applications. The stream processing system comprises astream processing operating environment, a controller configured toreceive a request for stream processing, a translation serviceconfigured to translate the request for stream processing into a formalexpression of the request in a description language, and a planninglibrary configured to generate a workflow based on the formal expressionof the request and a domain definition in the description language. Thedomain definition describes the stream processing operating environment.The workflow comprises nodes corresponding to stream processingapplication components with possible parameters values set and linkscorresponding to streams.

In other illustrative embodiments, the stream processing system performsvarious ones of the operations outlined above with regard to the methodin the illustrative embodiments.

In another illustrative embodiment, a computer program product forcomposing stream processing workflows using automatic planning comprisesa computer usable medium having computer usable program code embodiedtherein, computer usable program code configured to receive a requestfor stream processing in a stream processing system, wherein the streamprocessing system receives one or more primal streams and executesstream processing applications in a stream processing operatingenvironment, computer usable program code configured to translate therequest for stream processing into a formal expression of the request ina description language, and computer usable program code configured togenerate a workflow based on the formal expression of the request and adomain definition in the description language. The domain definitiondescribes the stream processing operating environment. The workflowcomprises nodes corresponding to stream processing applicationcomponents with possible parameters values set and links correspondingto streams.

In other illustrative embodiments, the computer program product furthercomprises computer usable program code configured to perform ones of theoperations outlined above with regard to the method in the illustrativeembodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features believed characteristic of the invention are setforth in the appended claims. The invention itself, however, as well asa preferred mode of use, further objectives and advantages thereof, willbest be understood by reference to the following detailed description ofan illustrative embodiment when read in conjunction with theaccompanying drawings, wherein:

FIG. 1 is a pictorial representation of a network of data processingsystems in which aspects of the present invention may be implemented;

FIG. 2 is a block diagram of a data processing system in which aspectsof the present invention may be implemented;

FIG. 3 illustrates an architecture for automatic composition of streamprocessing workflows satisfying output requirements expressed by endusers or systems in accordance with an exemplary embodiment of thepresent invention;

FIG. 4 illustrates an example of a stream processing workflow inaccordance with exemplary aspects of the present invention;

FIG. 5 illustrates an example of stream processing in accordance withexemplary aspects of the described embodiments;

FIGS. 6A-6D are example code fragments that illustrate definition ofdomain and the problem in a stream processing system in accordance withexemplary embodiments;

FIG. 7 is a block diagram illustrating an automated planning system inaccordance with an exemplary embodiment of the present invention;

FIG. 8 is a flowchart illustrating operation of an automated planningsystem for stream processing workflow composition in accordance with anexemplary embodiment; and

FIG. 9 is a flowchart illustrating operation of system state monitoringin accordance with one exemplary embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

With reference now to the figures and in particular with reference toFIGS. 1-2, exemplary diagrams of data processing environments areprovided in which embodiments of the present invention may beimplemented. It should be appreciated that FIGS. 1-2 are only exemplaryand are not intended to assert or imply any limitation with regard tothe environments in which aspects or embodiments of the presentinvention may be implemented. Many modifications to the depictedenvironments may be made without departing from the spirit and scope ofthe present invention.

FIG. 1 is a pictorial representation of a network of data processingsystems in which aspects of the present invention may be implemented.Network data processing system 100 is a network of computers in whichembodiments of the present invention may be implemented. Network dataprocessing system 100 contains network 102, which is the medium used toprovide communications links between various devices and computersconnected together within network data processing system 100. Network102 may include connections, such as wire, wireless communication links,or fiber optic cables.

In the depicted example, server 104 and server 106 connect to network102 along with storage unit 108. In addition, clients 110, 112, and 114connect to network 102. These clients 110, 112, and 114 may be, forexample, personal computers or network computers. In an exemplaryembodiment, server 104 may provide stream processing applications toclients 110, 112, and 114. Clients 110, 112, and 114 are clients toserver 104 in this example. Network data processing system 100 mayinclude additional servers, clients, and other devices not shown.

In one exemplary embodiment, network data processing system 100 is theInternet with network 102 representing a worldwide collection ofnetworks and gateways that use the Transmission ControlProtocol/Internet Protocol (TCP/IP) suite of protocols to communicatewith one another. At the heart of the Internet is a backbone ofhigh-speed data communication lines between major nodes or hostcomputers, consisting of thousands of commercial, governmental,educational and other computer systems that route data and messages. Ofcourse, network data processing system 100 also may be implemented as anumber of different types of networks, such as for example, an intranet,a local area network (LAN), or a wide area network (WAN). FIG. 1 isintended as an example, and not as an architectural limitation fordifferent embodiments of the present invention.

With reference now to FIG. 2, a block diagram of a data processingsystem is shown in which aspects of the present invention may beimplemented. Data processing system 200 is an example of a computer,such as server 104 or client 110 in FIG. 1, in which computer usablecode or instructions implementing the processes for embodiments of thepresent invention may be located.

In the depicted example, data processing system 200 employs a hubarchitecture including north bridge and memory controller hub (NB/MCH)202 and south bridge and input/output (I/O) controller hub (SB/ICH) 204.Processing unit 206, main memory 208, and graphics processor 210 areconnected to NB/MCH 202. Graphics processor 210 may be connected toNB/MCH 202 through an accelerated graphics port (AGP).

Local area network (LAN) adapter 212 connects to SB/ICH 204. Audioadapter 216, keyboard and mouse adapter 220, modem 222, read only memory(ROM) 224, hard disk drive (HDD) 226, CD-ROM drive 230, universal serialbus (USB) ports and other communication ports 232, and PCI/PCIe devices234 connect to SB/ICH 204 through bus 238 and bus 240. PCI/PCIe devicesmay include, for example, Ethernet adapters, add-in cards, and PC cardsfor notebook computers. PCI uses a card bus controller, while PCIe doesnot. ROM 224 may be, for example, a flash binary input/output system(BIOS).

HDD 226 and CD-ROM drive 230 connect to SB/ICH 204 through bus 240. HDD226 and CD-ROM drive 230 may use, for example, an integrated driveelectronics (IDE) or serial advanced technology attachment (SATA)interface. Super I/O (SIO) device 236 may be connected to SB/ICH 204.

An operating system runs on processing unit 206 and coordinates andprovides control of various components within data processing system 200in FIG. 2. As a client, the operating system may be a commerciallyavailable operating system such as Microsoft® Windows® XP (Microsoft andWindows are trademarks of Microsoft Corporation in the United States,other countries, or both). An object-oriented programming system, suchas the Java programming system, may run in conjunction with theoperating system and provides calls to the operating system from Javaprograms or applications executing on data processing system 200 (JAVAis a trademark of Sun Microsystems, Inc. in the United States, othercountries, or both).

As a server, data processing system 200 may be, for example, an IBM®eServer™ pSeries® computer system, running the Advanced InteractiveExecutive (AIX®) operating system or the LINUX® operating system(eServer, pSeries and AIX are trademarks of International BusinessMachines Corporation in the United States, other countries, or bothwhile LINUX is a trademark of Linus Torvalds in the United States, othercountries, or both). Data processing system 200 may be a symmetricmultiprocessor (SMP) system including a plurality of processors inprocessing unit 206. Alternatively, a single processor system may beemployed.

Instructions for the operating system, the object-oriented programmingsystem, and applications or programs are located on storage devices,such as HDD 226, and may be loaded into main memory 208 for execution byprocessing unit 206. The processes for embodiments of the presentinvention are performed by processing unit 206 using computer usableprogram code, which may be located in a memory such as, for example,main memory 208, ROM 224, or in one or more peripheral devices 226 and230.

Those of ordinary skill in the art will appreciate that the hardware inFIGS. 1-2 may vary depending on the implementation. Other internalhardware or peripheral devices, such as flash memory, equivalentnon-volatile memory, or optical disk drives and the like, may be used inaddition to or in place of the hardware depicted in FIGS. 1-2. Also, theprocesses of the present invention may be applied to a multiprocessordata processing system.

In some illustrative examples, data processing system 200 may be apersonal digital assistant (PDA), which is configured with flash memoryto provide non-volatile memory for storing operating system files and/oruser-generated data.

A bus system may be comprised of one or more buses, such as bus 238 orbus 240 as shown in FIG. 2. Of course, the bus system may be implementedusing any type of communication fabric or architecture that provides fora transfer of data between different components or devices attached tothe fabric or architecture. A communication unit may include one or moredevices used to transmit and receive data, such as modem 222 or networkadapter 212 of FIG. 2. A memory may be, for example, main memory 208,ROM 224, or a cache such as found in NB/MCH 202 in FIG. 2. The depictedexamples in FIGS. 1-2 and above-described examples are not meant toimply architectural limitations. For example, data processing system 200also may be a tablet computer, laptop computer, or telephone device inaddition to taking the form of a PDA.

FIG. 3 illustrates an architecture for automatic composition of streamprocessing workflows satisfying output requirements expressed by endusers in accordance with an exemplary embodiment of the presentinvention. To apply artificial intelligence automatic planningtechniques, the system must describe the initial state, the goal state,the conditions for applying each of the possible actions to the states,and the effects of each action. This may be done using a predicate-baseddescription language. The plan is defined as a sequence of actions thatlead from the initial state to a state that satisfies all goalrequirements.

Latest advances in artificial intelligence planning started with theapplication of plan graph analysis methods to planning. Application ofplan graph analysis essentially increased the size of planning problemsthat can be solved by automatic planners. Further development ofautomated planning systems was stimulated by introduction of a standardfor the description language for planning domains and planning problems.Planning is an important aspect of the autonomic computing model, and ithas always been considered as part of the autonomicmonitor-analyze-plan-execute using knowledge (MAPE-K) loop.

Recognition of the application of automatic planning to streamprocessing workflow composition is an important aspect of the presentinvention. Referring again to FIG. 3, end users/systems 310 providerequests to planner 315. The requests are goal-based problems to besolved by planner 315, which then generates plan graphs to execute inthe stream processing operating environment 320. Scheduler 325 deploysand schedules stream processing applications for execution within streamprocessing operating environment 320 on top of operating system andhardware 330. Stream processing operating environment 320 then returnsthe results to end users 310.

FIG. 4 illustrates an example of a stream processing workflow inaccordance with exemplary aspects of the present invention. Workflow 400receives as input one or more primal streams 410. A stream represents aflow of information satisfying certain restrictions or constraints. Anexample of the stream data may be a sequence of n-tuples of a predefinedformat. Primal streams 410 are streams that are received by the streamprocessing system, but are not generated within the stream processingsystem. Examples of primal streams include television audio and videoinformation, audio information from a radio broadcast, stock quotes andtrades, really simple syndication (RSS) feeds, and the like.

Stream processing application components 420 are configured to receive,analyze, and/or transform primal streams 410 to form resulting outputstreams 430. Application components 420 may be reusable components thatperform stream processing functions, such as, for example, videoprocessing, image analysis, speech-to-text conversion, text analytics,and the like. Each one of application components 420 may have one ormore inputs and one or more outputs.

The number of possible primal streams within primal streams 410 isenormous. Since stream processing application components 420 arepreferably reusable software components, they may be configured andreconfigured into many different workflows to form a seemingly limitlessnumber of stream processing applications. Also, the workflows may becomevery complex. For example, a given workflow may use tens of primalstreams and include hundreds, if not thousands, of applicationcomponents. To generate such a workflow by hand, and on demand, would bequite challenging if not simply impracticable. In fact, it is evendifficult to know all possible components and their parameters, muchless to be able to combine them into an effective workflow thatsatisfies all of the user's requirements.

FIG. 5 illustrates an example of stream processing in accordance withexemplary aspects of the described embodiments. In this example, enduser 550 requests to be notified when a particular stock is likely toexceed a predetermined value. Primal streams 510, 520, 530 includetrades, television news, and radio broadcasts. In the depicted example,application components include stock analytics 512, moving picturesexperts group 4 (MPEG-4) de-multiplexer 522, image analytics 524,speech-to-text conversion 526, text analytics 528, speech-to-textconversion 532, text analytics 534, and a stock model 540.

This stream processing application may be composed from existingapplication components, using available primal streams, such that theapplication components generate a result that satisfies the user'srequest. Thus, stock analytics component 512 receives trades informationstream 510 and outputs results to stock model component 540.

MPEG-4 de-multiplexer component 522 receives a television news broadcaststream 520 and outputs to image analytics component 524, text analyticscomponent 528, and speech-to-text conversion component 526.Speech-to-text conversion component 526, in turn, outputs to textanalytics component 528. Image analytics component 524 and textanalytics component 528 output to stock model component 540.

Speech-to-text conversion component 532 receives radio broadcast stream530 and outputs to text analytics component 534. In turn, text analyticscomponent 534 outputs to stock model 540. Stock model 540 providesoutput to user 550.

For stream processing workflow composition with automatic planning, thefollowing formal definitions are provided:

-   -   1. A data structure for describing stream content. This data        structure specifies values of predicates about certain        properties of the stream, as well as certain properties and        other types of descriptions. An example of a property is “video        of type MPEG-4.” A numeric property may be, for instance,        “throughput=10 KB/s.” This structure may be referred to as        stream properties.    -   2. An instance of stream properties structures is created and        initialized with appropriate values for each primal stream.    -   3. A formal description for each stream processing component.        Each description includes:        -   a. Definition of one or more input ports, where each input            port defines the conditions under which a stream can be            connected to the input port. In programming, a predicate is            a statement that evaluates an expression and provides a true            or false answer based on the condition of the data. These            conditions are expressed as logical expressions in terms of            stream properties. For example, a stream of type “video” may            be required on one port of a stream processing component,            and a stream of type “audio” on another.        -   b. Definition of one or more output ports, where each output            port definition describes a formula or a method for            computing all properties of the output stream, possibly            depending on the properties of all input streams connected            to the component.    -   4. Part of each end user's request for stream processing (goal)        is translated to a formal logical expression in terms of stream        properties that must be satisfied by the property values        associated with the output stream, or multiple output streams if        multiple goal definitions are given.

Given the above problem definition, where metadata descriptions 1-3 arereferred to as a “planning domain” and 4 is referred to as the “planningproblem,” the planning algorithm can compute properties of any streamproduced by a component or a combination of components applied to primalstreams, and verify whether goal requirements are satisfied. Forexample, the method of exhaustive search (depth-first or breadth-first)can be used to find a workflow that produces streams satisfying goalrequirements. In some systems, it is important to find workflows thatnot only satisfy the goal, but also satisfy additional criteria, such asoptimal quality or optimal resource usage. The same exhaustive searchmethod, or more efficient methods, may be used to achieve theseobjectives.

In one embodiment, the formal description of the workflow compositionproblem defined above may be encoded using planning domain definitionlanguage (PDDL), and submitted to a planning system, such as LPG-td,Metric-FF, or any other known planning system. LPG (Local search forPlanning Graphs) is a planner based on local search and planning graphsthat handles PDDL2.1 domains involving numerical quantities anddurations. The system can solve both plan generation and plan adaptationproblems. LPG-td is an extension of LPG to handle the new features ofthe standard planning domain description languages PDDL2.2. Metric-FF isa domain independent planning system developed by Jörg Hoffmann. Thesystem is an extension of the FF (Fast-Forward) planner to handlenumerical state variables, more precisely to PDDL 2.1 level 2, yet moreprecisely to the subset of PDDL 2.1 level 2 with algorithmic principles.

In one embodiment, stream properties may be encoded as fluents andpredicates parameterized with a stream object. Component descriptionsare encoded as actions parameterized with input and output streamobjects. Preconditions of actions consist of translated input portrequirements on input streams and action effects compute the propertiesof output stream objects with the transformation formulas associatedwith output ports. A plan generated by the planning system as a sequenceof actions is then translated into a workflow by identifyinginput-output port connections based on the sharing of stream objectsbetween instantiated action parameters corresponding to the port.

However, trying to implement automatic planning for stream processingworkflows using PDDL presents several difficulties. The facts that agiven stream contains some predicates and that the number of streams isrestricted only by equivalence relations dictates that a lot of space isrequired to describe all possible streams. An action of a component withmultiple inputs and outputs cannot be effectively decomposed into a setof actions with conjunctive form of conditional effects. Again, toaccurately represent stream processing components requires an enormousamount of space.

Therefore, in one exemplary embodiment, an enhanced description languageis provided. A stream processing planning language (SPPL) builds on theplanning domain description language to address the special needs ofstream processing workflow planning. XSPPL is a description language forstream processing workflow planning based on XPDDL, which is anextension of PDDL. Following is a description of the extensions to thedescription language for stream processing workflow planning.

Type represents a finite tree based on the inheritance relation. Onlysingle (not multiple) inheritance is allowed. Type object is a root typefor all types. Constants may be of certain types. The number ofconstants of a specific type may be high; however, that number isfinite. Variables may be named or not named. Unnamed variables are usedin the definition of the predicates and functions. Named variables areused in the actions definition.

Predicates represent variables on the system state. A predicate has adefinition and possibly an initial value. A stream represents a variableon the set of predicates. A stream is a special type of object. Forconvenience, a stream is considered as partially grounded (somevariables in the predicates signed) complete lists of predicates. SPPLand XSPPL identify two streams that incorporate identical predicates.SPPL and XSPPL use the notion of functions and elemental arithmeticoperations in the same way as PDDL [PDDL2.2]. Computing metrics, such asCPU utilization or memory requirements, are mapped into the planningfunctions.

Relations are fixed associations between the constants. Autonomicsystems make extensive use of the relation between user group and thecomponent set to which that group has access. Actions have preconditionsand effects. Both effects and preconditions are expressed in terms ofstreams. Each precondition is a set of expressions on a stream. SPPL andXSPPL consider the case of disjunctive preconditions for differentstreams. Each effect is a set of predicates associated with the stream,often dependent on preconditions.

FIGS. 6A-6D are example code fragments that illustrate definition ofdomain and the problem in a stream processing system in accordance withexemplary embodiments. More particularly, FIG. 6A illustrates theseparation of the planning task on domain definition and problemdefinition. FIG. 6B illustrates an example of a problem definition thatspecifies the state of the system in the beginning of the planningprocess. The illustrated problem definition also contains definition ofthe planning task goal. FIG. 6C depicts a streamed goal definition thatcontains description of goal for the planning task specified in theproblem definition file, as well as action definition defined in thedomain definition file. FIG. 6D illustrates an example of thedescription of the streamed action.

FIG. 7 is a block diagram illustrating an automated planning system inaccordance with an exemplary embodiment of the present invention.Message bus 710 busses messages from producers to consumers. Changecontroller 720 receives requests from users and change notificationsfrom message bus 710.

Change controller 720 uses translation service 730 to translate requestsfor planning into a description language. This description language maybe an existing description language, such as PDDL, or may be an extendeddescription language that addresses the specific needs of streamprocessing workflow composition, such as SPPL or XSPPL, which aredescribed above. The requests that are translated into a descriptionlanguage are then sent to planning library 734 as a problem definitionof the planning task.

Planning library 734 contains an algorithm for processing planningrequests formulated in a planning description language and produces aplan graph with nodes corresponding to components and linkscorresponding to streams. An example of a planning graph is illustratedin FIG. 4, described above. Plan adapter 740 adapts the plan graph tothe current configuration of operating environment 760.Deployer/scheduler 762 is used to provision and schedule plan executionin operating environment 760.

Monitor 764 monitors the state of operating environment 760 and persistsobserved state to system state database 756. Policies/profiles database752 stores user profiles and policies for stream processing. Examples ofpolicies are security policies like users from one department may haveall possible access. A user profile may contain a definition of a userrole and some possible exception that the user may have to access someextra information. Components description database 754 storesdescriptions of the stream processing application components. Changes todatabases 752, 754, 756 are sent through message bus 710 to changecontroller 720 as change notifications.

The contents of databases 752, 754, 756 represent the definitions ofuser profiles and policies, definitions of the application components,and the system state, respectively. This information together isreferred to as the “domain definition.” Translation service 730translates the domain definition into the planning description languageand stores the current domain definition in planning cache 732. Planningcache 732 is also updated upon notifications triggered by databasemodifications.

As stated above, change controller 720 receives direct requests forplanning from users. Change controller 720 also is able to resubmitrequests responsive to changes to profiles, policies, components, orsystem state. In this manner, a plan may be adjusted or adapted tochanges in the stream processing system on the fly. For example, if aprimal stream is no longer available, then the plan can be adjusted tosatisfy the user's request without the stream. As another example, if anew component becomes available, existing tasks can be re-planned totake advantage of the new component.

A solver component, such as planning library 734 in FIG. 7, for example,may exploit a model checking approach as an algorithm for the solver.The main properties of symbolic model checking include an ability todeal with possibly huge state spaces—usually characteristic ofcombinatorial explosion—and an ability to automatically take intoaccount internal symmetries, possibly hidden in the definitions of thepredicates and actions. Properties to be checked are represented ascomputational tree logic (CTL) formulas. Formalization allows reducingspace used, as each of the formulas represents a set of variablesinstead of individual variables.

Actions are represented as logical formulas. Logical formulas act astransformations on the state set. For the state variable s, its imageunder transformation T will be s′=Ts. The transformation formula isgiven by the following:

VΞ

T,D(T)

ssΛTs,

where Ξ is a set of all transformations and D(T) is a domain of thetransformation T.

The algorithm searches in the space of transitions of the state set. Thesearch starts from the initial state moving forward and from the goalstate moving backward. The search stops when the sequence elementstarted from initial state contains the sequence element started fromthe goal state (in this case, a feasible solution exists), or when bothof the sequences become cyclic (in this case, no feasible solutionexists).

Thereafter, the solution graph is extracted. Construction of thesolution progresses in two directions—starting from resulting point tothe initial and goal states. The resulting sequence of transformationsets forms the solution graph. An example data structure forrepresenting the state set in the symbolic logic is a binary decisiondiagram (BDD).

In this representation, a stream may contain multiple predicates. Thus,a stream is mapped naturally into the domain of variables. In dealingwith transition symmetry, the algorithm creates lookup tables for2-compositions of transition functions. Based on resource consumption,the algorithm optimizes the lookup table of equivalent compositions. Indealing with object symmetry, the algorithm analyzes a transition tableand defines groups of equivalent objects. During the transition stage,only one object from an equivalent group is used.

FIG. 8 is a flowchart illustrating operation of an automated planningsystem for stream processing workflow composition in accordance with anexemplary embodiment. FIG. 9 is a flowchart illustrating operation ofsystem state monitoring in accordance with one exemplary embodiment. Itwill be understood that each block of the flowchart illustrations, andcombinations of blocks in the flowchart illustrations, can beimplemented by computer program instructions.

These computer program instructions may be provided to a processor orother programmable data processing apparatus to produce a machine, suchthat the instructions that execute on the processor or otherprogrammable data processing apparatus create means for implementing thefunctions specified in the flowchart block or blocks. These computerprogram instructions may also exist within a computer-readable memory,storage, or transmission medium that can direct a processor or otherprogrammable data processing apparatus to function in a particularmanner. Instructions stored in a computer-readable memory or storagemedium produce an article of manufacture including instruction meanswhich implement the functions specified in the flowchart block orblocks.

Accordingly, blocks of the flowchart illustrations support combinationsof means for performing the specified functions, combinations of stepsfor performing the specified functions, and computer usable program codefor performing the specified functions. It will also be understood thateach block of the flowchart illustrations, and combinations of blocks inthe flowchart illustrations, can be implemented by special purposehardware-based computer systems that perform the specified functions orsteps, or by combinations of special purpose hardware and computerinstructions.

With particular reference to FIG. 8, operation begins and the automatedplanning system receives a goal-based request (block 802). The automatedplanning system translates the request into a planning descriptionlanguage (block 804) and sends the request to a planning library as aproblem definition (block 806). The automated planning system stores adomain definition in a planning cache (block 808).

The automated planning system generates a plan graph (block 810) andadapts the plan graph to the current configuration of the operatingenvironment (block 812). Next, the automated planning system deploys theadapted plan to the operating environment (block 814).

Then, the automated planning system determines whether a new request isreceived (block 816). If a new request is received, operation returns toblock 804 to translate the new request into the planning language (block804), and the operation is repeated for the new request. If a newrequest is not received in block 816, the automated planning systemdetermines whether a change notification is received (block 818). Achange notification may be received if there is a change in user profileor policy, a change in application component definitions, or a change insystem state. If a change notification is not received, operationreturns to block 816 and the automated planning system repeats blocks816 and 818 until a new request is received or a change notification isreceived. After a change notification is received, a determination ismade as to whether the notification requires a change in the domaindescription (820). If not, operation returns to block 816 to determinewhether a request is received.

If the automated planning system determines necessity of re-plan inresponse on change notification in block 820, then operation returns toblock 808 where the automated planning system stores an updated domaindefinition in the planning cache and generates a new plan graph (block810) for outstanding tasks affected by the change. Each new plan graphis then adapted (block 812) and deployed (block 814) for the updateddomain. In this manner, the automated planning system is able to reactto changes in the system state, new or unavailable primal streams orapplication components, and changes to user profiles and policiesautonomously.

Turning now to FIG. 9, a flowchart illustrating operation of systemstate monitoring is shown. Operation begins and the automated planningsystem monitors the system state (block 902). The automated planningsystem determines whether a change in state is encountered (block 904).If there is not a change in state, then operation returns to block 902to continue monitoring the system state.

If a change in state occurs in block 904, then the automated planningsystem persists the state to a system state database (block 906).Thereafter, the automated planning system generates a changenotification (block 908) and operation returns to block 902 to continuemonitoring the system state.

Automatic workflow composition results in cost savings due to eliminatedneed for specialized end user training or support personnel. The streamprocessing system with automatic planning is also self-healing. Thesystem also benefits from a reduced time of response to changes,increased reliability, reduced possibility of human error, and increasedsecurity, since a system that supports automatic composition allowsprotection of the information concerning system configuration optionsfrom the end user.

The invention can take the form of an entirely hardware embodiment, anentirely software embodiment or an embodiment containing both hardwareand software elements. In a preferred embodiment, the invention isimplemented in software, which includes but is not limited to firmware,resident software, microcode, etc.

Furthermore, the invention can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any tangibleapparatus that can contain, store, communicate, propagate, or transportthe program for use by or in connection with the instruction executionsystem, apparatus, or device.

The medium can be an electronic, magnetic, optical, electromagnetic,infrared, or semiconductor system (or apparatus or device) or apropagation medium. Examples of a computer-readable medium include asemiconductor or solid state memory, magnetic tape, a removable computerdiskette, a random access memory (RAM), a read-only memory (ROM), arigid magnetic disk and an optical disk. Current examples of opticaldisks include compact disk-read only memory (CD-ROM), compactdisk-read/write (CD-R/W) and DVD.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution.

Input/output or I/O devices (including but not limited to keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modem and Ethernet cards are just a few of thecurrently available types of network adapters.

The description of the present invention has been presented for purposesof illustration and description, and is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the art. Theembodiment was chosen and described in order to best explain theprinciples of the invention, the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

1. A method, in a stream processing system, for composing streamprocessing workflows using automatic planning, wherein the streamprocessing system receives one or more primal streams and executesstream processing applications in a stream processing operatingenvironment, the method comprising: receiving a request for streamprocessing; translating the request for stream processing into a formalexpression of the request in a description language; and generating aworkflow based on the formal expression of the request and a domaindefinition in the description language, wherein the domain definitiondescribes the stream processing operating environment, and wherein theworkflow comprises nodes corresponding to stream processing applicationcomponents with possible parameters values set and links correspondingto streams.
 2. The method of claim 1, further comprising: adapting theworkflow into a stream processing application that is executable in thestream processing operating environment.
 3. The method of claim 2,further comprising: deploying the stream processing application to thestream processing operating environment.
 4. The method of claim 1,further comprising: storing the domain definition in a planning cache.5. The method of claim 1, further comprising: receiving a changenotification that indicates one or more changes to the domaindefinition; and adjusting the workflow based on the one or more changesto the domain definition to form an adjusted workflow.
 6. The method ofclaim 5, further comprising: adapting the adjusted workflow into anadjusted stream processing application that is executable in theoperating environment.
 7. The method of claim 6, further comprising:deploying the adjusted stream processing application to the operatingenvironment.
 8. The method of claim 5, further comprising: determining anew domain definition in response to the change notification; andstoring the new domain definition in the planning cache.
 9. A streamprocessing system, for composing stream processing workflows usingautomatic planning, wherein the stream processing system receives one ormore primal streams and executes stream processing applications, thestream processing system comprising: a stream processing operatingenvironment; a controller configured to receive a request for streamprocessing; a translation service configured to translate the requestfor stream processing into a formal expression of the request in adescription language; and a planning library configured to generate aworkflow based on the formal expression of the request and a domaindefinition in the description language, wherein the domain definitiondescribes the stream processing operating environment, and wherein theworkflow comprises nodes corresponding to stream processing applicationcomponents with possible parameters values set and links correspondingto streams.
 10. The stream processing system of claim 9, furthercomprising: a plan adapter configured to adapt the workflow into astream processing application that is executable in the streamprocessing operating environment.
 11. The stream processing system ofclaim 10, further comprising: a scheduler configured to deploy thestream processing application to the stream processing operatingenvironment.
 12. The stream processing system of claim 9, a planningcache configured to store the domain definition in a planning cache. 13.The stream processing system of claim 9, wherein the controller isconfigured to receive a change notification that indicates one or morechanges to the domain definition; and wherein the planning library isconfigured to adjust the workflow based on the one or more changes tothe domain definition to form an adjusted workflow.
 14. The streamprocessing system of claim 13, wherein the plan adapter is configured toadapt the adjusted workflow into an adjusted stream processingapplication that is executable in the operating environment.
 15. Thestream processing system of claim 14, wherein the scheduler isconfigured to deploy the adjusted stream processing application to theoperating environment.
 16. The stream processing system of claim 13,wherein the planning cache stores a new domain definition responsive toreceipt of a change notification indicating a change in system state,user policy or profile, or component description.
 17. A computer programproduct for composing stream processing workflows using automaticplanning, the computer program product comprising: a computer usablemedium having computer usable program code embodied therein; computerusable program code configured to receive a request for streamprocessing in a stream processing system, wherein the stream processingsystem receives one or more primal streams and executes streamprocessing applications in a stream processing operating environment;computer usable program code configured to translate the request forstream processing into a formal expression of the request in adescription language; and computer usable program code configured togenerate a workflow based on the formal expression of the request and adomain definition in the description language, wherein the domaindefinition describes the stream processing operating environment, andwherein the workflow comprises nodes corresponding to stream processingapplication components with possible parameters values set and linkscorresponding to streams.
 18. The computer program product of claim 17,further comprising: computer usable program code configured to adapt theworkflow into a stream processing application that is executable in thestream processing operating environment.
 19. The computer programproduct of claim 18, further comprising: computer usable program codeconfigured to deploy the stream processing application to the streamprocessing operating environment.
 20. The computer program product ofclaim 17, further comprising: computer usable program code configured toreceive a change notification that indicates one or more changes to thedomain definition; and computer usable program code configured to adjustthe workflow based on the one or more changes to the domain definitionto form an adjusted workflow.